About me.

I’m a research scientist and engineer who turns open-ended questions into rigorous experiments, reproducible evidence, and working systems.

My work spans research science and research engineering: framing questions, designing evaluations, building experimental infrastructure, and communicating results with precision. I’ve applied that approach across AI safety, formal methods, database systems, and quantum optimization, producing first-author papers, open-source research artifacts, and production-minded tools. I currently work at NYU Tandon’s VIDA Center on DARPA’s expMath program, helping develop Lea as an open-source platform for mathematician-controlled formalization.

Our paper on tree-shaped substructures in property graphs was accepted at .

What I’m working on.

Current work in AI for mathematics, mechanistic interpretability, and agentic database optimization.

SystemAI for mathematics

Formalization with the mathematician in control.

I helped build Lea’s open-source platform for mathematician-controlled formalization in Lean at NYU Tandon’s VIDA Center through DARPA expMath. I am a first author on the accompanying paper, accepted to the Sixth Workshop on Mathematical Reasoning and AI at NeurIPS 2026.

Lea website ↗

ResearchAI safety

Mechanistic interpretability.

Studying how data provenance shapes shared parameter geometry in emergent misalignment, with a full-length manuscript under review at ICLR 2027. A separate Algoverse project investigates long-context alignment.

Work and research.

Roles, publications, projects, and education in one filterable view.

Research across AI safety, formal methods,
database systems, and quantum optimization.
Engineering across interfaces and infrastructure.

Core

Foundations and working tools.

Academic training, technical skills, and research methods behind the work above.

Computer science at NYU Courant.
Honours software engineering at McGill.
Tools for research and production.

Education

New York University

M.S. in Computer Science

Graduate School of Arts and Science · Courant Institute of Mathematical Sciences · School of Mathematics, Computing, and Data Science · New York City, NY · Fall 2026 – Present

McGill University

B.Sc. Honours Software Engineering

Montreal, Quebec · Graduated May 2026 · First Class Honours

3.99GPA / 4.0

Dean's ListAcademic award

Wing Hing ChanScholarship in Science

Distributed Systems (Grad) · Applied ML (Grad) · Computer Networks (Grad) · Sustainability for ML (Grad) · Algorithm Design · Operating Systems · Database Systems · Probability Theory · Statistics · Linear Algebra

Technical skills and research practice

Languages

Python · Java · C/C++ · OCaml · R · SQL · Cypher · JavaScript · Bash · Assembly · TypeScript · Swift · Lean

Machine Learning

PyTorch · TensorFlow · NumPy · pandas · scikit-learn · LoRA/PEFT · Transformers · CodeCarbon

Systems & Tools

React · Vite · FastAPI · Node.js · SQLite · Docker · GitHub Actions · Chrome Extensions · HTML/CSS · Git · LaTeX/Overleaf · Next.js · SwiftUI · Supabase · Lean 4

Concepts

Mech. Interp. · AI Safety · Fine-tuning · Distributed Computing · Graph Theory · Concurrency · Database Systems · Autoformalization · Formal Verification · Multi-Agent Systems · Human-AI Interaction · Event-Driven Architecture · Data Provenance

Research Practice

Literature Synthesis · Research Framing · Case-Study Design · Technical Writing · Reproducible Evaluation · Open-Source Communication